MEBN Understanding


TODOs

Developing MEBN understanding
Modeling a comprehensive real-life or hypothetical scenario using MEBN
Understanding of related concepts like Ontology, OOBN
Exploring different softwares (UnBBayes, Protégé etc)
PROLOG Recap

Sessions:

S#
Date
Discussions
Download Presentation
1
10/22/09
MEBN presentation first session conducted in which Predicate Logic, its limitations, BN limitations and need for MEBN language was discussed

2
10/24/09
MEBN presentation second session conducted in which architecture of MEBN ,
its recursive nature and generation of SSBN was discussed
same continued
3
10/24/09
PROLOG Session was conducted by sir to give us a brief overview of predicate logic

4
10/31/09
Predicate Logic Understanding was assigned to Saleha to explore it further and to understand what are the lackings of Predicate Logic. Thus as a part of project phase one Saleha took First Order Boolean Logic and its need

5
10/31/09
Object Oriented Bayesian Network understanding was assigned to Asma to explore its further and its usability as UnBBayes supports OOBN

6
12/05/09
MEBN Modelling Issues: Case study of Lahore Bombing was taken its BN model, OOBN model and BN model was drawn
BN

OOBN

MEBN

7
12/16/09
UnBBayes/PR-OWL Video Conferencing Session was conducted at IBA with Rommell Carvalho at GMU pursuing PhD. under Prof. Laskey. Clarifications of issues regarding MFragment, MThery and how to model in UnBBayes
Probabilistic Ontology Modeling Using UnBBayes - Part 1 of 10
Probabilistic Ontology Modeling Using UnBBayes - Part 2 of 10
Probabilistic Ontology Modeling Using UnBBayes - Part 3 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 4 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 5 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 6 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 7 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 8 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 9 of 10 Probabilistic Ontology Modeling Using UnBBayes - Part 10 o